Data processing systems are a staple of digital commerce, both private and commercial. Speed of data processing is important and has been addressed in a variety of different ways. In some instances, greater memory and central processing power are desirable, albeit at increased cost over system or systems with less memory and processing power.
Commerce, and indeed business in general is highly reliant on networked computer systems for nearly all aspects of business activity, such as offering products for sale, maintaining account records, analyzing data, etc. . . . Yet the needs for resources may and often do change from time to time.
Networks exist in a variety of forms, from the vast and expansive nature of the Internet to the small local area network of a company or home setting. Whereas it was once common place to provide all desired computer resources within one physical system, networking systems permit a greater flexibility in adaptively balancing resources and scaling to meet growing demands.
One type of networking resource that has grown in popularity is cloud computing. With respect to cloud storage, a user is permitted a great degree in terms of freedom to add or remove large or small quantities of data without incurring the direct costs of increasing hardware storage to accommodate larger volumes, or having available hardware resources available that are under utilized.
One popular form of cloud based storage is Amazon S3 (Simple Storage Service), an online web based storage service offered by Amazon Web Services. Amazon S3 provides a simple web service interface that permits users to store and retrieve virtually any amount of data, at any time and from anywhere on the Internet. Intended to provide high scalability, high availability and low latency, Amazon S3 has seen rise a number of related services that enhance or repackage the S3 functionality in different ways.
Although also intending to be low cost and perhaps indeed lower cost than providing localized storage, S3 architecture and other such cloud based storage systems operate in much the same way as traditionally expected storage systems, which is random access as permitted by a powered hard drive.
Random access is the ability to access different elements of data in an arbitrary position in a sequence in equal time, independent of the sequence size, and of course independent of the sequence order. This is the opposite from sequential access, wherein access time from one data element to the next is directly related to the distance between elements and is therefore not equal from any one element to any next element.
Often a user may have a considerable amount of legacy data that although desirable or perhaps even required to be maintained for some period of time is accessed very infrequently. In other cases, users may have an accumulation of data that although they desire its storage and access for retrieval, it is of low priority.
For such data, although the cloud based storage option of S3 or a similar service is perhaps desirable for its ease of access, an even lower cost option might be preferred as the frequency diminishes the value of S3's quick response time.
Yet, archiving out of the S3 environment may be undesirable as the action of archiving removes the general S3 functionality when and if it should be desired without having to first un-archive and restore data back into the S3 environment.
Moreover, although cloud based storage does provide improvement over localized storage in some ways, it is not without its own set of challenges and difficulties. Indeed the high scalability and flexibility of cloud based storage systems such as S3 are often highly desirable for active data management, when the frequency of use and or the type of use diminishes, the costs of traditional cloud base storage may become more noteworthy.
It is to innovations related to this subject matter that the claimed invention is generally directed.